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ruslanmv/all-MiniLM-L6-v2-ONYX
all-MiniLM-L6-v2-ONYX is a feature extraction model from ruslanmv. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as apache-2.0.
all-MiniLM-L6-v2-ONYX ==========================
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From the Hugging Face model README
Optimized Version of all-MiniLM-L6-v2 for Hugging Face Models
Author: Ruslan Magana Website: ruslanmv.com
The all-MiniLM-L6-v2-ONYX is an optimized version of the all-MiniLM-L6-v2 model, designed to provide super fast performance for Hugging Face models. This model is built upon the popular MiniLM-L6 architecture and fine-tuned for optimal performance.
Model Architecture*: MiniLM-L6
To use the all-MiniLM-L6-v2-ONYX model, simply install the Hugging Face Transformers library and load the model using the following code:
import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("all-MiniLM-L6-v2-ONYX")
tokenizer = AutoTokenizer.from_pretrained("all-MiniLM-L6-v2-ONYX")
This model is released under the Apache 2.0 license.
f you use the all-MiniLM-L6-v2-ONYX moden your research, please cite the following paper:
@article{wang2021minilm,
title={MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers},
author={Wang, W. and Joshi, F. and Liu, L. and Wu, R. and Wang, H.},
journal={arXiv preprint arXiv:2109.04263},
year={2021}
}
I would like to thank the Hugging Face team for providing the Transformers library and the MiniLM-L6 model.
For any questions or issues, please feel free to reach out to me at ruslanmv.com.
Please note that I had to make some assumptions about the model details, such as the number of parameters and model size, as this information was not provided. If you need to update these details, please let me know!